Computerized Decision-Support Systems for Chronic Pain Management in Primary Care

Toward a digital citizen lab for capturing data about alternative ways of self-managing chronic pain: An attitudinal user study

Background

Myriad psychosocial and cultural factors influence personal ways of coping with chronic pain (CP). Mobile health (mHealth) apps facilitate creation of citizen laboratories outside clinical frameworks. However, issues of safety, privacy and technostress must be addressed. This attitudinal user study aimed to assess whether persons with persistent pain (PwPP) would be open to sharing qualitative and quantitative data about their self-management of CP via mHealth platforms.

Methods

In March 2020, we invited PwPPs, their personal or medical caregivers, or those interested in the development of an app for researching alternative ways of self-managing CP to complete an anonymous survey. We formulated an attitudinal survey within the theoretical framework of stress to estimate whether the novelty, unpredictability, and risks of data-sharing via mHealth apps concerned users. Descriptive statistics (% Part/Group) were used to interpret the survey, and open comments were reflectively analyzed to identify emerging themes.

Results

Of 202 responses (June 2021), 127 identified as PwPPs (average age 43.86 ± 14.97; 100/127 female), and listed several primary and secondary CP diagnoses. In almost 90% of PwPPs, physical and emotional wellbeing were affected by CP. More than 90% of PwPPs used alternative therapies (acupuncture, homeopathy, massage therapy, etc.). Attitude toward mHealth apps were positive even though nearly half of PwPPs were unfamiliar with them. More than 72% of respondents were open to using a health-related app as a research tool for data collection in real life situations. Comprehensive data collection (especially about psychosocial factors) was the most important requirement. More respondents (especially medical professionals) were concerned about health hazards of misinformation communicated via health-related information and communication systems (maximum 80%) than about privacy (maximum 40%). Qualitative analyses revealed several promises and impediments to creation of data-sharing platforms for CP.

Conclusions

This study shows a general willingness among PwPPs to become partners in studying alternative pain management. Despite a generally positive attitude toward the concept of sharing complex personal data to advance research, heterogeneity of attitudes shaped by personal experiences must be considered. Our study underlines the need for any digital strategy for CP research to be person-centered and flexible.

The Case for the Anesthesiologist-Informaticist

Health care has been transformed by computerization, and the use of electronic health record systems has become widespread. Anesthesia information management systems are commonly used in the operating room to maintain records of anesthetic care delivery. The perioperative environment and the practice of anesthesia generate a large volume of data that may be reused to support clinical decision-making, research, and process improvement. Anesthesiologists trained in clinical informatics, referred to as informaticists or informaticians, may help implement and optimize anesthesia information management systems. They may also participate in clinical research, management of information systems, and quality improvement in the operating room or throughout a health care system. Here, we describe the specialty of clinical informatics, how anesthesiologists may obtain training in clinical informatics, and the considerations particular to the subspecialty of anesthesia informatics. Management of perioperative information systems, implementation of computerized clinical decision support systems in the perioperative environment, the role of virtual visits and remote monitoring, perioperative informatics research, perioperative process improvement, leadership, and change management are described from the perspective of the anesthesiologist-informaticist.

An Electronic Clinical Decision Support System for the Management of Low Back Pain in Community Pharmacy: Development and Mixed Methods Feasibility Study

Background

People with low back pain (LBP) in the community often do not receive evidence-based advice and management. Community pharmacists can play an important role in supporting people with LBP as pharmacists are easily accessible to provide first-line care. However, previous research suggests that pharmacists may not consistently deliver advice that is concordant with guideline recommendations and may demonstrate difficulty determining which patients require prompt medical review. A clinical decision support system (CDSS) may enhance first-line care of LBP, but none exists to support the community pharmacist–client consultation.

Objective

This study aimed to develop a CDSS to guide first-line care of LBP in the community pharmacy setting and to evaluate the pharmacist-reported usability and acceptance of the prototype system.

Methods

A cross-platform Web app for the Apple iPad was developed in conjunction with academic and clinical experts using an iterative user-centered design process during interface design, clinical reasoning, program development, and evaluation. The CDSS was evaluated via one-to-one user-testing with 5 community pharmacists (5 case vignettes each). Data were collected via video recording, screen capture, survey instrument (system usability scale), and direct observation.

Results

Pharmacists’ agreement with CDSS-generated self-care recommendations was 90% (18/20), with medicines recommendations was 100% (25/25), and with referral advice was 88% (22/25; total 70 recommendations). Pharmacists expressed uncertainty when screening for serious pathology in 40% (10/25) of cases. Pharmacists requested more direction from the CDSS in relation to automated prompts for user input and page navigation. Overall system usability was rated as excellent (mean score 92/100, SD 6.5; 90th percentile compared with similar systems), with acceptance rated as good to excellent.

Conclusions

A novel CDSS (high-fidelity prototype) to enhance pharmacist care of LBP was developed, underpinned by clinical practice guidelines and informed by a multidisciplinary team of experts. User-testing revealed a high level of usability and acceptance of the prototype system, with suggestions to improve interface prompts and information delivery. The small study sample limits the generalizability of the findings but offers important insights to inform the next stage of system development.

Design Process and Utilization of a Novel Clinical Decision Support System for Neuropathic Pain in Primary Care: Mixed Methods Observational Study

Background

Computerized clinical decision support systems (CDSSs) have emerged as an approach to improve compliance of clinicians with clinical practice guidelines (CPGs). Research utilizing CDSS has primarily been conducted in clinical contexts with clear diagnostic criteria such as diabetes and cardiovascular diseases. In contrast, research on CDSS for pain management and more specifically neuropathic pain has been limited. A CDSS for neuropathic pain has the potential to enhance patient care as the challenge of diagnosing and treating neuropathic pain often leads to tension in clinician-patient relationships.

Objective

The aim of this study was to design and evaluate a CDSS aimed at improving the adherence of interprofessional primary care clinicians to CPG for managing neuropathic pain.

Methods

Recommendations from the Canadian CPGs informed the decision pathways. The development of the CDSS format and function involved participation of multiple stakeholders and end users in needs assessment and usability testing. Clinicians, including family medicine physicians, residents, and nurse practitioners, in three academic teaching clinics were trained in the use of the CDSS. Evaluation over one year included the measurement of utilization of the CDSS; change in reported awareness, agreement, and adoption of CPG recommendations; and change in the observed adherence to CPG recommendations.

Results

The usability testing of the CDSS was highly successful in the prototype environment. Deployment in the clinical setting was partially complete by the time of the study, with some limitations in the planned functionality. The study population had a high level of awareness, agreement, and adoption of guideline recommendations before implementation of CDSS. Nevertheless, there was a small and statistically significant improvement in the mean awareness and adoption scores over the year of observation (P=.01 for mean awareness scores at 6 and 12 months compared with baseline, for mean adoption scores at 6 months compared with baseline, and for mean adoption scores at 12 months). Documenting significant findings related to diagnosis of neuropathic pain increased significantly. Clinicians accessed CPG information more frequently than they utilized data entry functions. Nurse practitioners and first year family medicine trainees had higher utilization than physicians.

Conclusions

We observed a small increase in the adherence to CPG recommendations for managing neuropathic pain. Clinicians utilized the CDSS more as a source of knowledge and as a training tool than as an ongoing dynamic decision support.

Impact of a Clinical Decision Support Tool on Cancer Pain Management in Opioid-Tolerant Inpatients

Background: Pain is both common and undertreated in the hematology/oncology population despite national guidelines and a focus from The Joint Commission. Objective: Herein, we describe the features of a pain clinical decision support tool (PCDST) embedded into the electronic medical record (EMR) and report its impact on oncology inpatients at risk for uncontrolled pain. Methods: The PCDST was developed to identify patients with potentially uncontrolled pain, defined as a pain score ≥4. Clinical pharmacists were encouraged to use the tool to determine whether interventions were needed to better control pain. Pain and safety outcomes between 2 cohorts of opioid-tolerant adult inpatients presenting with severe pain were compared prior to and following the implementation of the PCDST. Results: The primary endpoint, attainment of analgesia at 24 hours from admission, was met in 10 of 30 (33.3%) patients in the preimplementation group and in 14 of 32 (43.8%) of patients in the postimplementation group (P = .78). Secondary endpoints including time to analgesia, mean pain score, frequency of pharmacy intervention, and National Comprehensive Cancer Network (NCCN) guideline-adherent pain regimens were not found to be statistically significantly different between the 2 groups. The number of mean nursing pain assessments in the first 24 hours from admission was found to be significantly higher in the postimplementation group compared with the preimplementation group (12 vs 7.4, P < .001). Safety events were rare and not statistically different between groups. Conclusion: Overall, a modest, but statistically nonsignificant, improvement in pain outcomes was associated with patients admitted after the implementation of a pharmacist-managed electronic pain scoring tool.

Clinical Decision Support Tools for Selecting Interventions for Patients with Disabling Musculoskeletal Disorders: A Scoping Review

Purpose We aimed to identify and inventory clinical decision support (CDS) tools for helping front-line staff select interventions for patients with musculoskeletal (MSK) disorders. Methods We used Arksey and O'Malley's scoping review framework which progresses through five stages: (1) identifying the research question; (2) identifying relevant studies; (3) selecting studies for analysis; (4) charting the data; and (5) collating, summarizing and reporting results. We considered computer-based, and other available tools, such as algorithms, care pathways, rules and models. Since this research crosses multiple disciplines, we searched health care, computing science and business databases. Results Our search resulted in 4605 manuscripts. Titles and abstracts were screened for relevance. The reliability of the screening process was high with an average percentage of agreement of 92.3 %. Of the located articles, 123 were considered relevant. Within this literature, there were 43 CDS tools located. These were classified into 3 main areas: computer-based tools/questionnaires (n = 8, 19 %), treatment algorithms/models (n = 14, 33 %), and clinical prediction rules/classification systems (n = 21, 49 %). Each of these areas and the associated evidence are described. The state of evidentiary support for CDS tools is still preliminary and lacks external validation, head-to-head comparisons, or evidence of generalizability across different populations and settings. Conclusions CDS tools, especially those employing rapidly advancing computer technologies, are under development and of potential interest to health care providers, case management organizations and funders of care. Based on the results of this scoping review, we conclude that these tools, models and systems should be subjected to further validation before they can be recommended for large-scale implementation for managing patients with MSK disorders.

Interventions to improve safe and effective medicines use by consumers: an overview of systematic reviews

BACKGROUND

Many systematic reviews exist on interventions to improve safe and effective medicines use by consumers, but research is distributed across diseases, populations and settings. The scope and focus of such reviews also vary widely, creating challenges for decision-makers seeking to inform decisions by using the evidence on consumers' medicines use.This is an update of a 2011 overview of systematic reviews, which synthesises the evidence, irrespective of disease, medicine type, population or setting, on the effectiveness of interventions to improve consumers' medicines use.

OBJECTIVES

To assess the effects of interventions which target healthcare consumers to promote safe and effective medicines use, by synthesising review-level evidence.

SEARCH METHODS

We included systematic reviews published on the Cochrane Database of Systematic Reviews and the Database of Abstracts of Reviews of Effects. We identified relevant reviews by handsearching databases from their start dates to March 2012.

SELECTION CRITERIA

We screened and ranked reviews based on relevance to consumers' medicines use, using criteria developed for this overview.

DATA COLLECTION AND ANALYSIS

We used standardised forms to extract data, and assessed reviews for methodological quality using the AMSTAR tool. We used standardised language to summarise results within and across reviews; and gave bottom-line statements about intervention effectiveness. Two review authors screened and selected reviews, and extracted and analysed data. We used a taxonomy of interventions to categorise reviews and guide syntheses.

MAIN RESULTS

We included 75 systematic reviews of varied methodological quality. Reviews assessed interventions with diverse aims including support for behaviour change, risk minimisation and skills acquisition. No reviews aimed to promote systems-level consumer participation in medicines-related activities. Medicines adherence was the most frequently-reported outcome, but others such as knowledge, clinical and service-use outcomes were also reported. Adverse events were less commonly identified, while those associated with the interventions themselves, or costs, were rarely reported.Looking across reviews, for most outcomes, medicines self-monitoring and self-management programmes appear generally effective to improve medicines use, adherence, adverse events and clinical outcomes; and to reduce mortality in people self-managing antithrombotic therapy. However, some participants were unable to complete these interventions, suggesting they may not be suitable for everyone.Other promising interventions to improve adherence and other key medicines-use outcomes, which require further investigation to be more certain of their effects, include:· simplified dosing regimens: with positive effects on adherence;· interventions involving pharmacists in medicines management, such as medicines reviews (with positive effects on adherence and use, medicines problems and clinical outcomes) and pharmaceutical care services (consultation between pharmacist and patient to resolve medicines problems, develop a care plan and provide follow-up; with positive effects on adherence and knowledge).Several other strategies showed some positive effects, particularly relating to adherence, and other outcomes, but their effects were less consistent overall and so need further study. These included:· delayed antibiotic prescriptions: effective to decrease antibiotic use but with mixed effects on clinical outcomes, adverse effects and satisfaction;· practical strategies like reminders, cues and/or organisers, reminder packaging and material incentives: with positive, although somewhat mixed effects on adherence;· education delivered with self-management skills training, counselling, support, training or enhanced follow-up; information and counselling delivered together; or education/information as part of pharmacist-delivered packages of care: with positive effects on adherence, medicines use, clinical outcomes and knowledge, but with mixed effects in some studies;· financial incentives: with positive, but mixed, effects on adherence.Several strategies also showed promise in promoting immunisation uptake, but require further study to be more certain of their effects. These included organisational interventions; reminders and recall; financial incentives; home visits; free vaccination; lay health worker interventions; and facilitators working with physicians to promote immunisation uptake. Education and/or information strategies also showed some positive but even less consistent effects on immunisation uptake, and need further assessment of effectiveness and investigation of heterogeneity.There are many different potential pathways through which consumers' use of medicines could be targeted to improve outcomes, and simple interventions may be as effective as complex strategies. However, no single intervention assessed was effective to improve all medicines-use outcomes across all diseases, medicines, populations or settings.Even where interventions showed promise, the assembled evidence often only provided part of the picture: for example, simplified dosing regimens seem effective for improving adherence, but there is not yet sufficient information to identify an optimal regimen.In some instances interventions appear ineffective: for example, the evidence suggests that directly observed therapy may be generally ineffective for improving treatment completion, adherence or clinical outcomes.In other cases, interventions may have variable effects across outcomes. As an example, strategies providing information or education as single interventions appear ineffective to improve medicines adherence or clinical outcomes, but may be effective to improve knowledge; an important outcome for promoting consumers' informed medicines choices.Despite a doubling in the number of reviews included in this updated overview, uncertainty still exists about the effectiveness of many interventions, and the evidence on what works remains sparse for several populations, including children and young people, carers, and people with multimorbidity.

AUTHORS' CONCLUSIONS

This overview presents evidence from 75 reviews that have synthesised trials and other studies evaluating the effects of interventions to improve consumers' medicines use.Systematically assembling the evidence across reviews allows identification of effective or promising interventions to improve consumers' medicines use, as well as those for which the evidence indicates ineffectiveness or uncertainty.Decision makers faced with implementing interventions to improve consumers' medicines use can use this overview to inform decisions about which interventions may be most promising to improve particular outcomes. The intervention taxonomy may also assist people to consider the strategies available in relation to specific purposes, for example, gaining skills or being involved in decision making. Researchers and funders can use this overview to identify where more research is needed and assess its priority. The limitations of the available literature due to the lack of evidence for important outcomes and important populations, such as people with multimorbidity, should also be considered in practice and policy decisions.

Knowledge discovery in clinical decision support systems for pain management: a systematic review

OBJECTIVE

The occurrence of pain accounts for billions of dollars in annual medical expenditures; loss of quality of life and decreased worker productivity contribute to indirect costs. As pain is highly subjective, clinical decision support systems (CDSSs) can be critical for improving the accuracy of pain assessment and offering better support for clinical decision-making. This review is focused on computer technologies for pain management that allow CDSSs to obtain knowledge from the clinical data produced by either patients or health care professionals.

METHODS AND MATERIALS

A comprehensive literature search was conducted in several electronic databases to identify relevant articles focused on computerised systems that constituted CDSSs and include data or results related to pain symptoms from patients with acute or chronic pain, published between 1992 and 2011 in the English language. In total, thirty-nine studies were analysed; thirty-two were selected from 1245 citations, and seven were obtained from reference tracking.

RESULTS

The results highlighted the following clusters of computer technologies: rule-based algorithms, artificial neural networks, nonstandard set theory, and statistical learning algorithms. In addition, several methodologies were found for content processing such as terminologies, questionnaires, and scores. The median accuracy ranged from 53% to 87.5%.

CONCLUSIONS

Computer technologies that have been applied in CDSSs are important but not determinant in improving the systems' accuracy and the clinical practice, as evidenced by the moderate correlation among the studies. However, these systems play an important role in the design of computerised systems oriented to a patient's symptoms as is required for pain management. Several limitations related to CDSSs were observed: the lack of integration with mobile devices, the reduced use of web-based interfaces, and scarce capabilities for data to be inserted by patients.

Usability testing of a Smartphone for accessing a web-based e-diary for self-monitoring of pain and symptoms in sickle cell disease

We examined the usability of smartphones for accessing a web-based e-Diary for self-monitoring symptoms in children and adolescents with sickle cell disease (SCD). One group of participants (n = 10; mean age, 13.1 ± 2.4 y; 5 M; 5 F) responded to questions using precompleted paper-based measures. A second group (n = 21; mean age, 13.4 ± 2.4 y; 10 M; 11 F) responded based on pain and symptoms they experienced over the previous 12 hours. The e-Diary was completed with at least 80% accuracy when compared to paper-based measures. Symptoms experienced over the previous 12 hours included feeling tired (33.3%), headache (28.6%), coughing (23.8%), lack of energy/fatigue (19.0%), yellowing of the eyes (19.0%), pallor (19.0%), irritability (19.0%), stiffness in joints (19.0%), general weakness (14.3%), and pain (14.3%), rating on average as 2.0 ± 1.7 (on 0 to 10 scale). Overall, sleep was good (8.1 ± 1.4 on the 0 to 10 scale). In conclusion, children with SCD were able to use smartphones to access a web-based e-Diary for reporting pain and symptoms. Smartphones may improve self-reporting of symptoms and communication between patients and their health care providers, who may consequently be able to improve pain and symptom management in children and adolescents with SCD in a timely manner.

The impact of eHealth on the quality and safety of health care: a systematic overview

BACKGROUND

There is considerable international interest in exploiting the potential of digital solutions to enhance the quality and safety of health care. Implementations of transformative eHealth technologies are underway globally, often at very considerable cost. In order to assess the impact of eHealth solutions on the quality and safety of health care, and to inform policy decisions on eHealth deployments, we undertook a systematic review of systematic reviews assessing the effectiveness and consequences of various eHealth technologies on the quality and safety of care.

METHODS AND FINDINGS

We developed novel search strategies, conceptual maps of health care quality, safety, and eHealth interventions, and then systematically identified, scrutinised, and synthesised the systematic review literature. Major biomedical databases were searched to identify systematic reviews published between 1997 and 2010. Related theoretical, methodological, and technical material was also reviewed. We identified 53 systematic reviews that focused on assessing the impact of eHealth interventions on the quality and/or safety of health care and 55 supplementary systematic reviews providing relevant supportive information. This systematic review literature was found to be generally of substandard quality with regards to methodology, reporting, and utility. We thematically categorised eHealth technologies into three main areas: (1) storing, managing, and transmission of data; (2) clinical decision support; and (3) facilitating care from a distance. We found that despite support from policymakers, there was relatively little empirical evidence to substantiate many of the claims made in relation to these technologies. Whether the success of those relatively few solutions identified to improve quality and safety would continue if these were deployed beyond the contexts in which they were originally developed, has yet to be established. Importantly, best practice guidelines in effective development and deployment strategies are lacking.

CONCLUSIONS

There is a large gap between the postulated and empirically demonstrated benefits of eHealth technologies. In addition, there is a lack of robust research on the risks of implementing these technologies and their cost-effectiveness has yet to be demonstrated, despite being frequently promoted by policymakers and "techno-enthusiasts" as if this was a given. In the light of the paucity of evidence in relation to improvements in patient outcomes, as well as the lack of evidence on their cost-effectiveness, it is vital that future eHealth technologies are evaluated against a comprehensive set of measures, ideally throughout all stages of the technology's life cycle. Such evaluation should be characterised by careful attention to socio-technical factors to maximise the likelihood of successful implementation and adoption.